Create app.py

app.py

@@ -0,0 +1,26 @@
+import streamlit as st
+from transformers import pipeline
+
+# Title of the web application
+st.title('Chest and Physical Limitations LLM Query')
+
+# Initialize the model pipeline
+# Ensure to use the correct model identifier
+model_name = "Abbeite/chest_and_physical_limitations2"
+generator = pipeline('text-generation', model=model_name)
+
+# User prompt input
+user_prompt = st.text_area("Enter your prompt here:")
+
+# Button to generate text
+if st.button('Generate'):
+    if user_prompt:
+        # Generate response
+        try:
+            response = generator(user_prompt, max_length=50, clean_up_tokenization_spaces=True)
+            # Display the generated text
+            st.text_area("Response:", value=response[0]['generated_text'], height=250, disabled=True)
+        except Exception as e:
+            st.error(f"Error generating response: {str(e)}")
+    else:
+        st.warning("Please enter a prompt.")